WebAug 1, 2024 · Dynamic instance interactive head. Given N proposal boxes, Sparse R-CNN first utilizes the RoIAlign operation to extract features from backbone for each region defined with proposal bounding boxes ... WebMay 4, 2024 · Sparse R-CNN is a recent strong object detection baseline by set prediction on sparse, learnable proposal boxes and proposal features. In this work, we propose to improve Sparse R-CNN with two dynamic designs. First, Sparse R-CNN adopts a one-to-one label assignment scheme, where the Hungarian algorithm is applied to match only …
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WebRecent News. 01/2024: Our work on "Dynamic N:M Fine-grained Structured Sparse Attention Mechanism" appears in PPoPP'23.; 12/2024: Samsung MSL Funded Research Collaboration, 2024; 11/2024: Rensselaer-IBM AIRC Research Grant, 2024; 09/2024: Our work on "Dynamic Sparse Attention for Scalable Transformer Acceleration" appears on … WebJun 24, 2024 · Sparse R-CNN is a recent strong object detection baseline by set prediction on sparse, learnable proposal boxes and proposal features. In this work, we propose to improve Sparse R-CNN with two dynamic designs. First, Sparse R-CNN adopts a one-to-one label assignment scheme, where the Hungarian algorithm is applied to match only … dates world cup games
Structured Sparse R-CNN for Direct Scene Graph Generation
WebSparse R-CNN is a recent strong object detection baseline by set prediction on sparse, learnable proposal boxes and proposal features. In this work, we propose to improve Sparse R-CNN with two dynamic designs. First, Sparse R-CNN adopts a one-to-one label assignment scheme, where the Hungarian algorithm is applied to match only one … WebWe present Sparse R-CNN, a purely sparse method for object detection in images. Existing works on object detection heavily rely on dense object candidates, such as k anchor … WebMay 4, 2024 · Particularly, Dynamic Sparse R-CNN reaches the state-of-the-art 47.2% AP on the COCO 2024 validation set, surpassing Sparse R-CNN by 2.2% AP with the same … bj brown omaha ne